QSAR modeling of anticancer activity of heterocyclichydrazone

Abstract

In this study, validated PLS-DA models that discriminate heterocyclichydrazones with potent anticancer activity (GI50/IC50<50x10-6M) from those with low activity (GI50/IC50>=50x10- 6M) against the cancer cell lines HCT-116 (colon), OVCAR-8 (human ovary), HL-60 (leukemia), and SF-295 (glioblastoma) were developed. A dataset of 24-a-(N)-heterocyclichydrazones and 14 N-acylhydrazonyl-thienyl and various global and local reactivity descriptors were used for modeling. The best models classified for training and test sets with an accuracy range between 67-100%, a class specificity and sensitivity range between 71-100%, error rate range between 0-0.27, and nonerror rate range between 0.73-1.0. An external set of 20 compounds was predicted and the models showed which new compounds are not suggested for further biological investigation. The molecular properties with impact on the modeled endpoints show that the antitumor activity can be improved with electron-acceptor N-acylhydrazonyl-thienyl derivatives and a-(N)-heterocyclichydrazones with moderate electron-donating character.